Evaluating the Marketing Communication Strategy of Volkswagen in Post-Crisis Period: Application of Image Repair Theory
Bibliographic record
Abstract
This case study focuses on effective marketing communication activities in a post-crisis period. The phenomenon underpinning the investigation is image repair theory which provides effective communication strategies to overcome these events. The case in point was the emission scandal faced by Volkswagen (VW) in 2015. By implementing a qualitative approach to data collection and analysis, the results showed some correlations between effective public relation activities and the company’s share price. Nevertheless, sales figures showed a negative attribute due to the unstable position of the company in the post scandal period. Results also showed a positive pattern when VW responded to the emission scandal in the early days, providing some strategies to stakeholders such as, mortification, reducing offensiveness and corrective action. However, it can be said that this study is an initial step which provides some indications for future research concerning the effective implementation of marketing communication in a post-scandal period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".